Is citizen science ethical?

I was really surprised the first time someone asked — I think it was in a review of a proposal — about whether it was ethical to do citizen science. “Isn’t this exploitation?” was how the concern was phrased. Getting unpaid people to do what was previously paid work might seem problematic. As citizen science has grown, so too has thoughtful criticism of the practice.

The term ‘citizen science’ covers such a wide range of activities that I think it’s hard to address the ‘ethics of citizen science’ broadly. As citizen science is broad, so too are its ethics, covering everything from completely ethical to unethical.

First, my favorite type of ‘citizen science’: volunteers take part in some part of the scientific process. They are not monetarily compensated, and instead the rewards are such things as authentic contribution to science knowledge, access to and communication with professional scientists, community belonging, and fun. My first citizen science project Snapshot Serengeti falls nicely into this category. The volunteers enjoy the project so much that when they’ve finished classifying a batch of wildlife images, they beg us to give them more images to classify. This is clearly not exploitation. And I feel it’s quite ethical.

One could actually posit, though: is it ethical to scientists to allow unpaid non-professionals to assist with the science process. In theory, if it became widespread enough, unpaid volunteers have the potential to do work that is currently done right now by undergraduates, graduate students, and technicians, potentially reducing job availability. I honestly think that this won’t happen. There is so much potential work to be done that citizen scientists don’t pose a job security risk to anyone in the science pipeline. For Snapshot Serengeti, we tried to use undergraduates. But even though we had a dozen of them, we still didn’t have enough person-power to go through our millions of images.

Okay, next up: ‘citizen science’ that I more generally refer to as ‘crowdsourcing’. In these types of activities, people are paid small amounts of money (or other tangible compensation) to do a tiny slice of science work, such as classifying a single image or answering a single question, typically online.

This practice of piecemeal work was revolutionized by the Amazon Mechanical Turk marketplace, which facilitated its broad-scale adoption. However, the general concept of small payments in exchange for a small amount of data has been around for a long time. As an undergrad, did you ever participate in the psychology department’s experiments? I did. You got $5 or $10 for participating in whatever short experiments they were conducting at the time. More recently, I’ve signed my kids up for experiments at Harvard’s child development center — you get $5 and parking. Hardly worth the monetary compensation, but I find it really neat to see what they’re investigating. The social sciences have been using this general practice for decades and now have fully embraced Mechanical Turk (a 2012 how-to paper has more than 900 citations). They have also been thinking about theethicalimplications.

There are issues of low wages, lack of protection for workers, and general lack of oversight. On the other hand, it’s not entirely clear how Mechanical Turk workers are using the site. The workers are NOT all low-income people in poor countries struggling to get by and trying to do solely using Mechanic Turk. In fact, I imagine it’s very likely that many workers are squeezing Mechanical Turk work in between other obligations when they otherwise wouldn’t have generated any income — stay-at-home parents during children’s nap times, employed people during their bus commute, etc. For these people, this practice is highly beneficial. My general feeling is that a scientist ought to be thinking hard about ethics if they go the piecemeal work route for citizen science, because the ethics are a bit murky and the potential for exploitation is real.

Lastly: ‘citizen science’ as education. Most funding for citizen science at the national scale is for educational purposes (for example, this recent NSF Dear Colleague Letter). I love the idea of people learning more about science through doing actual real research. However, I worry a lot about so-called ‘citizen science’ that asks volunteers to do unpaid work that results in data that are never used. In my mind, this is not citizen science at all, but rather very elaborate lab experiments. Science knowledge — not just data — must be the result for an activity to be called ‘citizen science,’ in my mind. However, educational funding opportunities typically do not provide the necessary support for post-collection data use, including both careful design to ensure usable data and the human resources necessary to analyze the data — and do something with it (publish, provide feedback to managers or policy-makers, etc.). Volunteers generally don’t sign up because they want to be educated at, they sign up because they want to make a difference, because they want to contribute. Asking volunteers to engage in authentic science research and then throwing away their efforts is, in my mind, unethical. And it happens (quietly) too often. (I should be careful here to note that some primarily educational citizen science projects do produce usable data and do make an effort to turn that data into shared knowledge. And I think those projects are great and ethical.)

I’m sorry you’ve had this experience. Disagreements (sometimes acrimonious) over credit also happen in professional science. The best way to avoid it is to have clear communication before any discoveries happen about how credit is given. I think this is something that citizen science is starting to learn, but obviously there needs to be more thought about it for many (most?) projects.

thanks for putting this post; i’m exploring such issues as part of my research about using online learning platforms to teach people and do massive citizen science at the same time! here’s a recent paper: vineetp13.github.io/publications/CHI2017-GutInstinct-Creating_scientific_theories_with_online_learners.pdf